4 citations · 9 across the 8 of their papers we have counts for
4 papers · 1 filter
Multi-Agent Framework for Threat Mitigation and Resilience in AI-Based Systems
Armstrong Foundjem, Lionel Nganyewou Tidjon, Leuson Da Silva +1
Machine learning (ML) underpins foundation models in finance, healthcare, and critical infrastructure, making them targets for data poisoning, model extraction, prompt injection, a…
AI Benchmark Democratization and Carpentry
Gregor von Laszewski, Wesley Brewer, Jeyan Thiyagalingam +28
Benchmarks are a cornerstone of modern machine learning, enabling reproducibility, comparison, and scientific progress. However, AI benchmarks are increasingly complex, requiring d…
Risk Management for Mitigating Benchmark Failure Modes: BenchRisk
Sean McGregor, Victor Lu, Vassil Tashev +8
Large language model (LLM) benchmarks inform LLM use decisions (e.g., "is this LLM safe to deploy for my use case and context?"). However, benchmarks may be rendered unreliable by…
Adversarial Attack Classification and Robustness Testing for Large Language Models for Code
Yang Liu, Armstrong Foundjem, Foutse Khomh +1
Large Language Models (LLMs) have become vital tools in software development tasks such as code generation, completion, and analysis. As their integration into workflows deepens, e…